Data Platform Architecture

Assumptions about Data Platform Architecture

  1. Scaling-Out is better than scaling up.
  2. In-Memory is better than on disk (spinning or otherwise).
  3. Having data hosted within your control plane or tenant, either on-premises or in the cloud (AWS, Azure, GCP) gives you more control and visibility into the security and access for this data than data hosted in someone else’s control-plane or tenant.
  4. A Data Lakehouse (Data Lake + Data Warehouse) architecture is superior to either a Data Lake alone or a Data Warehouse alone.
  5. Having fewer Code Bases, Tools, Components, Models (Data Models, Security Models, Metadata Models, Data Glossaries, Data Dictionaries, Data Ranking, Data Quality, etc.) is better than duplicating them across Code Bases, Tools, Components, and Models.
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